People with bipolar disorder are more likely to die at a younger age compared with the general population (Crump et al 2013; Hoang et al 2013). This is often due to high rates of suicide and violent crime, which I blogged about last year, but may also be attributed to a heightened risk for physical health problems.

In 2013, Rethink published a report (PDF) outlining a number of common factors which can lead to medical illnesses in this population such as smoking, side effects from antipsychotic medication, as well as poor physical health monitoring and stigma.

Hayes and colleagues (2015) conducted a systematic review and meta-analysis of large observational studies to estimate the mortality rate of people with bipolar disorder compared with the general population. They looked at a range of different reasons for mortality which included unnatural causes, such as suicide and violent crime, as well as natural causes, such as circulatory and respiratory problems.

The lower life expectancy for people with bipolar disorder is a result of high rates of suicide and violent crime, as well as a heightened risk of physical health problems.

Methods

The authors looked for eligible articles by searching three electronic databases, scanning reference lists of included studies and tracking citations using the Cochrane Database of Systematic Reviews and Google Scholar.

Studies were included if they reported data on deaths of people with a diagnosis of bipolar disorder (any criteria were accepted), due to any reason (all-cause mortality) or deaths due to specific reasons (cause-specific mortality) including:

Natural deaths

Unnatural deaths

Suicide

Other violent deaths

Infection

Neoplasm

Respiratory

Circulatory system disease

Studies were excluded if they had fewer than 50 participants or were not standardised by age.

Standardised mortality ratios (SMRs) with their 95% confidence intervals were used to calculate the ratio of participants with bipolar disorder who died for each reason compared with the general population. SMRs greater than 1 indicate increased mortality in people with bipolar disorder compared with the general population, whereas those smaller than 1 indicate decreased mortality in this population.

Heterogeneity within each meta-analysis was assessed using the I2 index and chi-square test. Additionally a number of meta-regressions were carried out for all-cause mortality controlling for: decade of publication, cohort size, geographical region, mid-decade of cohort data collection and population type (inpatient or community based). Subgroup analyses where also performed for geographical region of study, patient population type and decade of the middle year of patient observation.

Results

In total, 31 studies of 305,859 people with bipolar disorder met the inclusion criteria. Studies were mainly inpatient cohorts (64%) and a large proportion were conducted in Scandinavian countries (45%).

All-cause mortality

The SMR for all-cause mortality was 2.05 (95% CI 1.98 to 2.23), ranging from 1.24 (95% CI 0.83 to 1.17) to 4.65 (95% CI 1.27 to 11.91). Heterogeneity between studies was significant and high (p < 0.001, I2 =96.2%).

Cause-specific mortality

SMRs indicated increased rates of death for people with bipolar disorder for all cause-specific mortality categories. Estimates were highest for death due to suicide (SMR=14.44) and unnatural causes (SMR=7.42). As for all-cause mortality, heterogeneity was significant and high for most categories except for infection and neoplasm which were relatively homogenous.

Cause-specific mortality

Summary SMR (95% CI)

Natural

1.64 (1.47 to 1.83)

Unnatural

7.42 (6.43to 8.55)

Suicide

14.44 (12.43to 16.78)

Other violent

3.68 (2.77to 4.90)

Circulatory

1.73 (1.54to 1.94)

Respiratory

2.92 (2.00to 4.23)

Infection

2.25 (1.70to 3.00)

Neoplasm

1.14 (1.10to 1.21)

Meta-regression and sub-group analyses

Meta-regression analyses revealed that none of the following variables could account for the heterogeneity in findings: decade of publication, cohort size, geographical region, mid-decade of cohort data collection or population type. Subgroup analyses also did not find any effect on heterogeneity when stratifying for geographical region, population type and mid-decade of study.

People with bipolar disorder have over twice the all-cause mortality compared with the general population.

Conclusions

The authors concluded that:

This meta-analysis highlights differential mortality in patients with bipolar disorder and the general population. Similarly to schizophrenia, patients with bipolar disorder have over twice the all-cause mortality. Mortality from all physical conditions and unnatural causes is elevated. Variation in all-cause mortality is considerable across time and place. There is no evidence that all-cause mortality for patients with bipolar disorder has improved over time relative to the general population.

Strengths and limitations

The authors carried out a thorough search strategy using multiple databases and tracking citations from reference lists of included studies. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement and the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) proposal for reporting were also followed. However, despite being an item in both reporting checklists, the authors did not carry out an assessment of study quality, which may have played a role in the high levels of heterogeneity found.

Another limitation in this review is the fact that included studies only adjusted SMRs for age and gender. It therefore was not possible to assess whether other factors may have accounted for the increased rate of deaths or heterogeneity in findings. For example, people with a serious mental illness are more likely to smoke which may have had a significant impact on deaths due to respiratory problems.

Summary

Overall this review provides evidence that people with bipolar disorder have increased mortality rates compared with the general population.

For all-cause mortality, there was a two-fold increase, whereas for suicide the SMR was as high as 14, which reflects previous results from large cohort studies. Although there was considerable heterogeneity in the summary estimate, all studies showed an increased risk for all-cause mortality of which only 4 out of 31 showed confidence intervals which crossed the line of no effect. These studies were all relatively small (74-440 participants) which explains the large confidence intervals. This finding indicates that we can be fairly certain that a true increased risk exists, although the precise estimate is still uncertain.

An interesting finding was that when controlling for year of publication, there was no effect on estimates indicating no change in mortality ratios from 60 years ago with those completed recently. This highlights the need for improvements in physical and mental health monitoring, smoking cessation programmes and the provision of clear information about side effects of medication.

The reviewers found no change in mortality ratios for people with bipolar disorder over the last 60 years.

If you need help

If you need help and support now and you live in the UK or the Republic of Ireland, please call the Samaritans on 116 123.

Elena is a research assistant at the National Collaborating Centre for Mental health and University College London. She has completed a BSc in Psychology at Warwick University and an MSc in Psychiatric Research at the Institute of Psychiatry (King’s College London). Her role currently involves reviewing evidence for the development of NICE clinical guidelines. These have recently included: Bipolar disorder (update), Antenatal and Postnatal Mental Health (update) and Challenging Behaviour and Learning Disabilities. Her research interests include stigma and discrimination, psychological therapies for serious mental illness, and service user empowerment and patient choice in care and treatment.

We welcome The Mental Elf’s interest in our meta-analysis. I have addressed what seems to be the main criticism of the paper: lack of an exploration of study quality, in a response to a letter in the publishing journal:

We considered assessing methodological quality via a tool such as the Newcastle–Ottawa Scale. However, many of the points included in this tool are not applicable to the studies in question, for example definition of outcome (always death) or definition of control population (always mortality in the country of study). We also considered adding that studies needed to have explicit inclusion/exclusion criteria and operationalised diagnostic criteria to be considered ‘high quality’. However, this tended to make scores more similar; single site studies of in-patient populations score well on these criteria, whereas population-based cohorts score badly (despite population-based cohorts clearly being more generalisable). Universally reported factors that could introduce biased estimates were assessed, these included the following: country of study, year of publication, years of data collection, factors for standardisation, site of data collection (population, single site and multisite), population type (in-patient or community). We did not feel combining these factors into a ‘score’ would have improved the analysis or its interpretation.

One of the main aims of the analysis was to see if the heterogeneity in SMR estimates could be explained by the factors available, and it could not.

Regarding the comment by @seenafazel, whilst it is true some deaths may have been double counted because of overlapping time periods we were sufficiently convinced that the benefits of including both studies outweighed the risks of biased summary estimates. Often we made this decision because studies included SMR estimates for different cause-specific mortalities, or there were differences in the source bipolar populations (for example in the case of Crump et al. vs Laursen et al. one is a pure inpatient cohort, the other a community and inpatient mix) , or differences in the general population from which the SMR is calculated. This is evident in the heterogeneity of the SMR estimates from these studies. Stratification by geographical region also showed Nordic countries to have the most heterogeneous SMR estimates, and these are the only countries in which double counting may have been an issue, because of the use of large electronic health record databases.

If double counting occurred, this would be true for both the population with bipolar disorder and the general population. Therefore it would reduce the standard error rather altering the point estimate when combing studies. The use of a random effects model then limits this possible error by including the within study and between study variance. The random effects model assumes that the studies differ from each other in ways that could impact the effect estimate. As always, cautious interpretation of the summary SMR is necessary: it is the estimate of the mean of distribution of SMRs, rather than an estimate of the true effect size. Given these points, our aim was to understand where the heterogeneity was coming from, rather than describe one “true” SMR for bipolar disorder.

Presumably if the focus is in examining sources of heterogeneity, then including overlapping samples may hinder that. For example, Laursen, Osby and Westman will include large numbers of the same patients with bipolar disorder. That will hide some of the real heterogeneity between the samples. Same applies to the overlapping Danish samples.

[…] People with bipolar disorder or schizophrenia (often referred to as severe mental illness, or SMI) die on average 10-20 years sooner than the general population. This difference in life expectancy is commonly known as the ‘mortality gap’. It has been a consistent research finding for years (Hayes, Miles, Walters, King, & Osborn, 2015). This study by Joseph Hayes et al, published in the British Journal of Psychiatry, compares changing death rates in population groups from 2000 to 2014. It is accompanied by an editorial on the same topic by Siddiqi et al. Other Elves have also written blogs on this subject (Elena Marcus, 2015). […]